Evidence map›Paper›PMID 35369114›Full record

ArticlePreventive medicine reports2022

Completeness of cohort-linked U.S. Medicare data: An example from the Agricultural Health Study (1999-2016).

Christine G Parks, Srishti Shrestha, Stuart Long, Thomas Flottemesch, Sarah Woodruff, Honglei Chen, Gabriella Andreotti, Jonathan N Hofmann, Laura E Beane Freeman, Dale P Sandler

Abstract read
In one paragraph

Article in Preventive medicine reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Christine G ParksEpidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA.
Srishti ShresthaFormerly of the Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA.
Stuart LongWestat, Rockville, MD, USA.
Thomas FlottemeschDLH, Silver Spring, MD, USA.
Sarah WoodruffWestat, Rockville, MD, USA.
Honglei ChenDepartment of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, East Lansing, MI, USA.
Gabriella AndreottiOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Jonathan N HofmannOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Laura E Beane FreemanOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
Dale P SandlerEpidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA.

Funding

Health Effects Of Exposures In AgricultureZIAES049030 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI SANDLER, DALE P · 2009 to 2025
$11.2M
STUDIES OF OCCUPATIONAL CANCER--PESTICIDESZ01CP010119 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI ALAVANJA, MICHAEL · 1996 to 2008
$5.0M
HEALTH EFFECTS OF EXPOSURES IN AGRICULTUREZ01ES049030 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI SANDLER, DALE P · 1997 to 2008
$889k
Intramural NIH HHS Z01 CP010119Intramural NIH HHS Z01 ES049030
6 · The paper itself

Abstract

Medicare Fee for Service (FFS) claims data, including inpatient (Part A) and outpatient (Part B) services, provide a valuable resource for research on older adults (≥65 year) in linked U.S. cohorts. Here we describe our experience linking the Agricultural Health Study cohort, including 47,501 licensed pesticide applicators and spouses from North Carolina (NC) and Iowa (IA) to Medicare claims data from 1999 to 2016. Given increased Part C (i.e., managed care/Medicare Advantage) enrollment during this period, and a resulting lack of available Part C claims data prior to 2015, we also explored potential for informative missingness. We compared those with partial or limited/no FFS to those with complete FFS coverage (i.e., ≥11 months per year parts AB, but not C, throughout Medicare enrollment) in relation to baseline farm size, general pesticide use, and mortality, in logistic regression models adjusted for age, sex, race, education, and smoking, and stratified by state. While 46,689 participants (98%) were linked to Medicare IDs, only 33,487 (70%) had complete FFS, 9353 (20%) had partial FFS (≥1 year FFS but not complete), and 3849 (8%) had limited/no FFS (Part A or Part C-only). Incomplete FFS was more common in NC, mostly due to Part C, and was associated with farm characteristics, pesticide use, and mortality. These findings indicate that, in addition to reduced sample size in analyses limited to complete FFS, missingness may not be random. The potential impact of incomplete FFS data and changes in coverage type need to be considered when planning linked analyses and interpreting results.

Indexed as

ACA, Affordable Care ActCMS, Centers for Medicare and Medicaid ServicesCohort studyFarmersFFS, Fee for serviceLinked dataMedicareMMA, Medicare Modernization ActRuralSSN, Social Security Number

Identifiers

PMID35369114
PMCPMC8971642

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.